Cancer Research Center, Cancer Institute of Iran, Tehran University of Medical Sciences, Tehran, Iran; Department of Medical Immunology, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.
Uro-Oncology Research Center, Tehran University of Medical Sciences, Tehran, IR, Iran.
Comput Biol Med. 2022 Feb;141:105043. doi: 10.1016/j.compbiomed.2021.105043. Epub 2021 Nov 20.
BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is one of the common subtypes of kidney cancer. Circular RNAs (circRNAs) act as competing endogenous RNAs (ceRNAs) to affect the expression of microRNAs (miRNAs), and hence the expression of genes involved in the development and progression of ccRCC. However, these interactions have not been sufficiently explored. METHODS: The differential expression of circRNAs (DEC) was extracted from the GEO database, and the expression of circRNAs was analyzed by the Limma R package. The interaction of miRNAs with circRNAs was predicted using (cancer-specific circRNA database) CSCD and circinteractome database. The genes affected by the miRNAs were predicted by miRwalk version 3, and the differential expression was retrieved using TCGA. Functional enrichment was assessed and a PPI network was created using DAVID and Cytoscape, respectively. The genes with significant interactions (hub-genes) were screened, and the total survival rate of ccRCC patients was extracted from the Gene Expression Profiling Interactive Analysis (GEPIA) database. To confirm the expression of OS genes we used the Immunohistochemistry (IHC) data and TCGA database. The correlation between gene expression and immune cell infiltration was investigated using TIMER2.0. Finally, potential drug candidates were predicted by the cMAP database. RESULTS: Four DECs (hsa_circ_0003340, hsa_circ_0007836, hsa_circ_0020303, and hsa_circ_0001873) were identified, along with 11 interacting miRNAs (miR-1224-3p, miR-1294, miR-1205, miR-1231, miR-615-5p, miR-940, miR-1283, and miR-1305). These miRNAs were predicted to affect 1282 target genes, and function enrichment was used to identify the genes involved in cancer biology. 18 hub-genes (CCR1, VCAM1, NCF2, LAPTM5, NCKAP1L, CTSS, BTK, LILRB2, CD53, MPEG1, C3AR1, GPR183, C1QA, C1QC, P2RY8, LY86, CYBB, and IKZF1) were identified from a PPI network. VCAM1, NCF2, CTSS, LILRB2, MPEG1, C3AR1, P2RY8, and CYBB could affect the survival of ccRCC patients. The hub-gene expression was correlated with tumor immune cell infiltration and patient prognosis. Two potantial drug candidates, naphazoline and lithocholic acid could play a role in ccRCC therapy, as well other cancers. CONCLUSION: This bioinformatics analysis brings a new insight into the role of circRNA/miRNA/mRNA interactions in ccRCC pathogenesis, prognosis, and possible drug treatment or immunotherapy.
背景：透明细胞肾细胞癌（ccRCC）是肾癌的常见亚型之一。环状 RNA（circRNA）作为竞争性内源 RNA（ceRNA）发挥作用，影响 microRNA（miRNA）的表达，从而影响 ccRCC 发生发展相关基因的表达。然而，这些相互作用尚未得到充分探索。
方法：从 GEO 数据库中提取差异表达的 circRNAs（DEC），并使用 Limma R 包分析 circRNAs 的表达。使用（癌症特异性 circRNA 数据库）CSCD 和 circinteractome 数据库预测 miRNA 与 circRNAs 的相互作用。使用 miRwalk 版本 3 预测受 miRNA 影响的基因，并使用 TCGA 检索差异表达。使用 DAVID 和 Cytoscape 分别进行功能富集评估和 PPI 网络构建。筛选具有显著相互作用的基因（hub-genes），并从 Gene Expression Profiling Interactive Analysis（GEPIA）数据库中提取 ccRCC 患者的总生存率。为了验证 OS 基因的表达，我们使用免疫组织化学（IHC）数据和 TCGA 数据库。使用 TIMER2.0 研究基因表达与免疫细胞浸润的相关性。最后，使用 cMAP 数据库预测潜在的药物候选物。
结果：鉴定出 4 个 DEC（hsa_circ_0003340、hsa_circ_0007836、hsa_circ_0020303 和 hsa_circ_0001873）和 11 个相互作用的 miRNA（miR-1224-3p、miR-1294、miR-1205、miR-1231、miR-615-5p、miR-940、miR-1283 和 miR-1305）。这些 miRNA 被预测影响 1282 个靶基因，功能富集用于鉴定参与癌症生物学的基因。从 PPI 网络中鉴定出 18 个 hub-genes（CCR1、VCAM1、NCF2、LAPTM5、NCKAP1L、CTSS、BTK、LILRB2、CD53、MPEG1、C3AR1、GPR183、C1QA、C1QC、P2RY8、LY86、CYBB 和 IKZF1）。VCAM1、NCF2、CTSS、LILRB2、MPEG1、C3AR1、P2RY8 和 CYBB 可影响 ccRCC 患者的生存。hub-基因表达与肿瘤免疫细胞浸润和患者预后相关。两个潜在的药物候选物，萘甲唑啉和石胆酸可能在 ccRCC 治疗以及其他癌症中发挥作用。
结论：这项生物信息学分析为 circRNA/miRNA/mRNA 相互作用在 ccRCC 发病机制、预后和可能的药物治疗或免疫治疗中的作用提供了新的见解。
Zhong Nan Da Xue Xue Bao Yi Xue Ban. 2022-4-28
Front Chem. 2023-10-11
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